Self-regulated Learning Activities Research Articles

Effect of self-regulated learning and technology-enhanced activities on anatomy learning, engagement, and course outcomes in a problem-based learning program.

Problem-based learning (PBL) offers advantages for teaching anatomy and physiology for physical therapy students as clinical cases provide a scaffold for a comprehensive review of body systems. Although the utilization of interactive anatomy software greatly contributes to an active learning environment and efficient use of time, simply providing textbook readings, access to anatomy software, and models is not enough to engage students to become active in reaching their learning goals. Time constraints, meaningful technology implementation, resource abundance, and unfamiliarity are challenges that decrease the effectiveness of both facilitating and learning anatomy. The present study investigated the use of three supplemental learning tools to support anatomy instruction in a self-regulated manner. Friedman test results demonstrated significant differences for perceived engagement [χ2(2) = 15.74, P < 0.001, W = 0.23] but not for perceived learning. Survey responses demonstrated that perceived engagement was greatest with the nondigital supplemental learning tool compared with the two technology-enhanced learning tools (iBooks Author + SoftChalk and SoftChalk alone). Multivariate regression analyses demonstrated statistically significant relationships between the nondigital supplemental learning tool and anatomy practical scores (P < 0.001). The technology-enhanced supplemental learning tools did not further increase learning outcomes as measured by practical scores compared with nondigital learning tools. Incorporation of instructor-created instructional materials independent of technology is an efficient method to drive self-regulated learning, enhance engagement, and improve anatomy course outcomes and may overcome barriers associated with a purely self-directed PBL model.

The effects of self-monitoring on strategy use and academic performance: A meta-analysis

Metacognitive monitoring and control lie at the core of self-regulated learning activities. However, the impact of self-monitoring on academic performance remains to be quantified. The present meta-analysis systematically reviewed 36 experimental studies (N = 2617), with 27 studies testing the effects of self-monitoring on strategy use and 30 studies testing the effects of self-monitoring on academic performance. Results showed that self-monitoring intervention had positive, moderate effects on strategy use (Hedges' g = 0. 38, 95% CI [0.25; 0.50]) and academic performance (Hedges' g = 0.47, 95%CI [0.33; 0.61]). Furthermore, mediator analyses revealed that self-monitoring intervention had greater effects on strategy use when it was embedded into a multi-component intervention. Also, stronger effects on academic performance were associated with environment support from multiple sources. Taken together, these results suggest that self-monitoring is an effective approach to promote strategy use and academic performance. Practical implications include designing and implementing self-monitoring interventions in an integrative approach and a support system.

Time Perspectives as The Predictors of Online Self-Regulated Learning

Digital education considerably requires active participation of students in the learning process, the application of self-regulated learning activities for the attainment of successful learning results. The aim of the present study is the investigation of time perspectives as the predictors of online self-regulated learning. In our study 210 Transylvanian students participated, from the Babes-Bolyai University, Faculty of Psychology and Educational Sciences. Students’ demographic characteristics were recorded, for the assessment of self-regulation the Self-regulated Online Learning Questionnaire - Revised was applied and time perspectives of students were measured by the Zimbardo Time Perspective Inventory. A correlational, cross-sectional design was used. On the basis of the results of hierarchical regression, in our first model demographic characteristics explained 5% of the variance for the application of self-regulation activities. In our second model, controlling demographic variables, time perspectives explained an additional 33% of the variance for self-regulation. Self-regulated learning strategies are predicted among demographic characteristics by students’ gender, age and online learning, while out of time perspectives only future orientation proved to be a significant predictor. Females, older students, participants attending online education and higher future orientation apply to a higher degree the self-regulated learning strategies as males, younger students and participants with lower scores at future orientation.

Temporal Assessment of Self-Regulated Learning by Mining Students’ Think-Aloud Protocols

It has been widely theorized and empirically proven that self-regulated learning (SRL) is related to more desired learning outcomes, e.g., higher performance in transfer tests. Research has shifted to understanding the role of SRL during learning, such as the strategies and learning activities, learners employ and engage in the different SRL phases, which contribute to learning achievement. From a methodological perspective, measuring SRL using think-aloud data has been shown to be more insightful than self-report surveys as it helps better in determining the link between SRL activities and learning achievements. Educational process mining on the basis of think-aloud data enables a deeper understanding and more fine-grained analyses of SRL processes. Although students’ SRL is highly contextualized, there are consistent findings of the link between SRL activities and learning outcomes pointing to some consistency of the processes that support learning. However, past studies have utilized differing approaches which make generalization of findings between studies investigating the unfolding of SRL processes during learning a challenge. In the present study with 29 university students, we measured SRL via concurrent think-aloud protocols in a pre-post design using a similar approach from a previous study in an online learning environment during a 45-min learning session, where students learned about three topics and wrote an essay. Results revealed significant learning gain and replication of links between SRL activities and transfer performance, similar to past research. Additionally, temporal structures of successful and less successful students indicated meaningful differences associated with both theoretical assumptions and past research findings. In conclusion, extending prior research by exploring SRL patterns in an online learning setting provides insights to the replicability of previous findings from online learning settings and new findings show that it is important not only to focus on the repertoire of SRL strategies but also on how and when they are used.

How Technology Tools Impact Writing Performance, Lexical Complexity, and Perceived Self-Regulated Learning Strategies in EFL Academic Writing: A Comparative Study.

Students experience different levels of autonomy based on the mediation of self-regulated learning (SRL), but little is known about the effects of different mediation technologies on students' perceived SRL strategies. This mixed explanatory study compared two technology mediation models, Icourse (a learning management system) and Icourse+Pigai (an automatic writing evaluation system), with a control group that did not use technology. A quasi-experimental design was used, which involved a pre and post-intervention academic writing test, an SRL questionnaire, and one-to-one semi-structured student interviews. The aim was to investigate 280 Chinese undergraduate English as a foreign language (EFL) students' academic writing performance, lexical complexity, and perceptions of self-regulated strategies in academic writing. One-way ANCOVA of writing performance, Kruskal-Wallis test of lexical complexity, ANOVA of the SRL questionnaire, and grounded thematic content analysis revealed that, first, both Icourse and Icourse+Pigai provided significant support for the development of SRL strategies vs. the control group, although there was no significant difference between the two groups. Second, Icourse+Pigai-supported SRL was more helpful for improving students' academic writing performance because it enabled increased writing practice and correction feedback. Third, Icourse+Pigai-supported SRL did not significantly improve students' lexical complexity. In conclusion, we argue that both learning management systems and automated writing evaluation (AWE) platforms may be used to assist students' SRL learning to enhance their writing performance. More effort should be directed toward developing technological tools that increase both lexical accuracy and lexical complexity. We conclude that the technical tools used in this study were positively connected to the use of SRL techniques. However, when creating technologically mediated SRL activities, students' psychological study preferences should be considered.

Informal academic learning space preferences of tertiary education learners

PurposeThis paper aims to address tertiary education informal learning space preferences for learners’ informal learning activities. The study accentuates learners’ preferred informal academic learning space (IALS) for informal learning activities that required interaction and communication and collaboration.Design/methodology/approachThe research is based on a survey questionnaire that participated by 1,079 diploma learners from Polytechnics’ technical and non-technical academic programmes in Malaysia.FindingsThe finding reveals that learners mostly preferred IALS that were categorized as semi-outdoor and connected to nature. Learners prefer to have IALS for collaborative learning activities with the appropriate information, communication and technology facilities and thermally conductive. Learners preferred an attractive layout design with comfortable furniture for informal learning activities. Apparently, learning space design is more focused on formal learning rather than informal learning.Originality/valueThis study grants a profound insight centred upon the learner’s perspective on the spatial alignment of education 4.0 learning ecosystem can be configured to enhance collaborative and self-regulated learning activities by distinguishing the critical preference of IALS.

Metacognitive Awareness and Academic Self-Regulation of HEI Students

The presented manuscript has analysed the theoretical aspects of the concepts of metacognitive awareness and academic self-regulation of HEI students. A theoretical essence of the mentioned above phenomena has been theoretically studied. The role and importance of metacognitive awareness and its components for the learning efficiency and academic self-regulation of HEI students have been described. It has been determined that such a metacognitive characteristic of personality as metacognitive awareness determines not only the organization of mental and behavioral processes, but also relates to the academic success of the subject of learning activity - student. The results of empirical research with the use of Questionnaire “Academic Self-Regulation” by R. Ryan &amp; D. Connell, Questionnaire “Metacognitive Awareness Inventory” by D. Everson &amp; S. Tobias, G. Schraw &amp; R. Dennison’s questionnaire “Metacognitive awareness”, and correlation analysis with the use of the Pearson’s and Spearmen’s rank correlation coefficients, have proved that students with a high level of metacognitive awareness (involvement in activities) have high performance on the basis of identified and internal self-regulated learning activities. The students of this type are more autonomous in conducting their self-regulated learning activities, developing their metacognitive abilities, such as metacognitive knowledge, metacognitive monitoring, metamemory and meta-thinking. Summarizing the results of theoretical analysis and the empirical data evaluation, we can conclude that the learning behavior of modern student youth has been dominated by dependent types of self-regulation.

Facilitating goal setting and planning to enhance online self-regulation of learning

Online learning environments demand learners to self-regulate their learning but many learners are poor at self-regulated learning (SRL). In this paper, two studies were conducted to examine the effect of two SRL supports, i.e., guiding goal setting and planning using an approach known as mental contrasting and implementation intentions (MCII) and prompting SRL using videos, on motivation in the form of task value and self-efficacy, SRL in the form of persistence, task strategies, self-evaluation, and self-satisfaction, student engagement, performance, and goal attainment. In Study 1, a two (MCII, no MCII) by two (prompt, no prompt) between-subjects controlled experiment was conducted in an online video-based learning environment. Results showed that learners who completed the MCII had more sustained task value and higher persistence than learners who did not receive the MCII. Study 2 was conducted in five Massive Open Online Courses where we compared three conditions: MCII, goal only, and control. Results showed that there were no significant differences in SRL activities, course engagement and performance, and goal attainment among the three conditions. Collectively, the results suggest that the task duration in which learners’ goals can be attained (e.g., within one short session or over multiple weeks) might influence the effectiveness of MCII.

Secondary students’ online self-regulated learning during flipped learning: A latent profile analysis

Flipped learning (FL) makes greater use of students' self-regulated learning (SRL) skills when they regulate their online learning behavior. Previous research has shown the value of SRL support during FL to enhance students' SRL and learning outcomes. However, as previous studies have indicated that SRL behavior varies, should SRL support be tailored to these differences in SRL? We applied latent profile analysis to identify subgroups in 150 eighth-graders during FL. We used practically relevant online behavioral data to represent students’ online SRL activities, which we gathered unobtrusively in an ecologically valid secondary educational classroom setting. We found five distinct SRL profiles from low completion and no activity to full completion and very high activity. In addition, students in the profile who showed low SRL activity achieved significantly worse learning outcomes than students in the three profiles with higher SRL activity. Finally, we explored whether SRL activity profile membership can be explained by student characteristics (i.e., self-reported SRL, motivation, and prior knowledge). None of the student-level variables predicted profile membership, but our approach offers leads for future research to further investigate the potential of tailored SRL support.

An analysis of internal and external feedback in self-regulated learning activities mediated by self-regulated learning tools and open learner models

In self-regulated learning (SRL), students organize, monitor, direct, and regulate their learning. In SRL, monitoring plays a critical role in generating internal feedback and thus adopting appropriate regulations. However, students may have poor SRL processes and performance due to their poor monitoring. Researchers have suggested providing external feedback to facilitate better student SRL. However, SRL involves many meta-cognitive internal processes that are hidden and difficult to observe and measure. This study proposed a SRL model to illustrate the relationship among external SRL tools, internal SRL processes, internal feedback, and external feedback. Based on the model, this study designed a system with SRL tools and open leaner models (OLMs) to assist students in conducting SRL, including self-assessing their initial learning performance (i.e. perceived initial performance and monitoring of learning performance) after listening to a teacher’s lecture, being assessed by and receiving external feedback from the OLM (i.e. actual performance) in the system, setting target goals (i.e. desired performance) of follow-up learning, conducting follow-up learning (i.e. strategy implementation), and evaluating their follow-up learning performance (i.e. perceived outcome performance and strategy outcome monitoring). These SRL tools also externalize students’ internal SRL processes and feedback, including perceived initial, desired, and perceived outcome performances, for investigation. In addition, this study explores the impact of external feedback from the OLM on students’ internal SRL processes and feedback. An evaluation was conducted to record and analyze students’ SRL processes and performance, and a questionnaire was administered to ask students about their SRL processes. There are three main findings. First, the results showed that students often have poor internal SRL processes and poor internal feedback, including poor self-assessment, inappropriate target goals, a failure to conduct follow-up learning, and a failure to achieve their goals. Second, the results revealed that the SRL tools and external feedback from the OLM assisted most students in SRL, including monitoring their learning performance, goal-setting, strategy implementation and monitoring, and strategy outcome monitoring. Third, some students still required further support for SRL.

Self-regulation and emotion matter: A case study of instructor interactions with a learning analytics dashboard

Learning analytics (LA) is providing new methodologies that are being applied to the design and application of dashboards to support teaching and learning. However, few studies attempt to understand how instructors interact with an LA dashboard and how self-regulated learning (SRL) activities and emotions of instructors occur and co-occur in the interaction. The current study investigates ten instructors’ SRL activities and epistemic emotions by analyzing the screen capture videos and think-aloud data while they interact with an LA dashboard designed to support the online asynchronous collaboration of multiple groups. The results reveal that instructors demonstrated two ways of navigating LA dashboards, and they relied heavily on the conversation explorer feature. Instructors were mostly engaged in elaboration, monitoring, and evaluation activities and they frequently experienced confusion and enjoyment. Expert instructors were more likely to refer to their personal teaching experience and demonstrated more epistemic emotions than novice instructors. This study contributes to the literature on SRL and teacher emotions by revealing the critical role of elaboration, monitoring, evaluation, and epistemic emotions when instructors attempt to understand a LA dashboard by themselves. These findings highlight the importance of providing pedagogical assistance to teachers who are trying to navigate between group dynamics and visualizations viewed using LA dashboards.

Examining the use of prompts to facilitate self-regulated learning in Massive Open Online Courses

The limited instructional support in Massive Open Online Courses (MOOCs) inherently demands learners to self-regulate their learning. MOOC research shows that learners are more successful when they engage in self-regulated learning (SRL) behaviors such as planning what to study and reviewing study materials. However, many learners struggle with SRL. In this study, we examined the effect of two types of SRL prompts (i.e., questions or a combination of questions and recommendations) on SRL activities, course engagement, and performance in MOOCs. Learners either received questions supporting SRL, questions supporting SRL followed by recommendations, or neither questions supporting SRL nor recommendations. Log data was used to examine learners’ behavior in the MOOCs. Results showed the SRL prompts, in general, are effective in enhancing SRL-related activities and course engagement. However, the effectiveness of the SRL prompts may be influenced by the complexity of the MOOCs. The current study adds to the field of SRL by examining prompting as an approach to enhance SRL in MOOCs.

Factors that impact social networking in online self-regulated learning activities

Among the literature on self-regulated learning and social networking, the studies, which explore the impact of social networks on learning regarding connection sizes and relationship-establishing factors, are rarely seen in the context of social networking among strangers. This descriptive study addresses the gap by exploring data from 468 Chinese junior high school graduates in an online learning resource platform with an integrated social network. The data is digitally generated when the graduates engaged in online self-regulated learning activities for an average of 36 days without any facilitations. The data analysis explores the connection sizes and types of follow links, types of self-regulated learners, and their relationship with lesson completion. The study reveals that social networks trigger different levels of learning engagement. Specifically, the graduates with bidirectional follow links and the optimal connection size of five complete more lessons than other graduates. The study also finds that academic factors (similar learning goals and achievement gaps) are more important than social factors (common identity) in establishing social connections to support self-regulated learning activities. These findings have direct implications for the design of social networking that facilitates self-regulated learning, and enhances students’ self-regulated learning efficacy in online learning environments.

Facilitating Success: Using Self-Regulated Learning and Servant Leadership in the College Classroom

&#x0D; Student-centered pedagogy shifts the power dynamics, function of content, role of the educator, responsibility for learning, and purpose of evaluation within the classroom. By redirecting student effort toward self -regulated learning activities within a learning management system (LMS), educators can focus on the application of material during in-person class meetings. Moving from a traditional role of lecturing to a more contemporary role of facilitating learning , educators are better equipped to embrace the philosophy of a servant leader and put student needs first through the utilization of self-regulated learning activities within an LMS. This reflective essay will focus on the application and benefit of self -regulated learning activities with a focus on the use of LMS-based activities and a flipped-classroom&#x0D; strategy utilized by two business communications faculty members. The discussion of classroom activities and online self-regulated learning activities will be backed up with research related to reports of student stress levels decreasing, connection to educators increasing, and student engagement levels increasing with the use of student-centered pedagogy and servant teaching practices in the college classroom.&#x0D;

Mine the process: investigating the cyclical nature of upper primary school students’ self-regulated learning

The present study investigates primary school students’ self-regulated learning (SRL) process by exploring the sequence in which SRL activities are conducted during learning. The aims of this study are twofold: investigating the presence of the theoretically hypothesized cyclical nature in students’ SRL process, as well as potential differences herein for high, average, and low achievers. Think-aloud data of 104 upper primary school students were analysed by means of process mining analysis. The results indicate that students commonly adopt a cyclical approach to learning by implementing preparatory, performance, and appraisal activities during learning. However, the results indicate clear differences in the quality of students’ SRL process. High achievers, compared to low and average achievers, show a more strategic and adaptive approach to learning during all phases of their learning process. They more strategically and effectively orient on and plan assignments, combine different cognitive strategies, and adopt self-evaluation to regulate their learning process.

The role of self-regulated learning on science and design knowledge gains in engineering projects

ABSTRACTResearch on self-regulated learning (SRL) in engineering design is growing. While SRL is an effective way of learning, however, not all learners can regulate themselves successfully. There is a lack of research regarding how student characteristics, such as science knowledge and design knowledge, interact with SRL. Adapting the SRL theory in the field of engineering design, this study proposes a research model to examine the mediation and causal relationships among science knowledge, design knowledge, and SRL activities (i.e. observation, formulation, reformulation, analysis, evaluation). Partial least squares modeling was utilized to examine how the science and design knowledge of 108 ninth-grade participants interacted with their SRL activities in the process of performing an engineering task. Results reveal that prior science and design knowledge positively predict SRL activities. They also show that reformulation and analysis are the two SRL activities that can lead to an improvement in post science and design knowledge, but excessive observation can hinder post design knowledge. These results have important implications for the construction of learning environments to support SRL based on students’ prior knowledge levels.

A mixed method approach to studying self-regulated learning in MOOCs

To be successful in online education, learners should be able to self-regulate their learning due to the autonomy offered to them. Accurate measurement of learners’ self-regulated learning (SRL) in online education is necessary to determine which learners are in need of support and how to best offer support. Trace data is gathered automatically and unobtrusively during online education, and is therefore considered a valuable source to measure learners’ SRL. However, measuring SRL with trace data is challenging for two main reasons. First, without information on the how and why of learner behaviour it is difficult to interpret trace data correctly. Second, SRL activities outside of the online learning environment are not captured in trace data. To address these two challenges, we propose a mixed method approach with a sequential design. Such an approach is novel for the measurement of SRL. We present a pilot study in which we combined trace data with interview data to analyse learners’ SRL in online courses. In the interview, cued retrospective reporting was conducted by presenting learners with visualizations of their trace data. In the second part of the interview, learners’ activities outside of the online course environment were discussed. The results show that the mixed-method approach is indeed a promising approach to address the two described challenges. Suggestions for future research are provided, and include methodological considerations such as how to best visualize trace data for cued retrospective recall.&nbsp;&nbsp;

Mathematical connection ability in 7th grade students viewed from self-regulated learning

The purpose of this research is to determine which mathematical connection ability is better; students with high, medium or low self-regulated learning. This research was descriptive quantitative research. The instruments used in this research were questionnaire of self-regulated learning and written test of mathematical connection ability. The research samples consisted of 186 students who were studying at a state Junior High School in Sukoharjo Regency, Indonesia, with heterogeneous abilities. The data analysis technique used was one-way Anova with unbalanced cell and post hoc test using the Scheffe method. The results show that students with high self-regulated learning have better mathematical connection ability than students with medium and low self-regulated learning. Students with medium self-regulated learning have better mathematical connections ability than students with low self-regulated learning. In order to connect to each mathematical problem, students must first remember the problem, while to understand the problem, students must be able to make connections with topics related to the problem so that students’ efforts in finding solutions to mathematical problems are through self-regulated learning activities. When students have self-regulated learning, they will significantly improve their mathematical connection ability.

Supporting learners' self-regulated learning in Massive Open Online Courses

In MOOCs, learners are typically presented with great autonomy over their learning process. Therefore, learners should engage in self-regulated learning (SRL) in order to successfully study in a MOOC. Learners however often struggle to self-regulate their learning. We implemented an SRL intervention in three MOOCs. The intervention consisted of three short videos containing SRL instruction and study suggestions to improve learners' SRL. We tested the effects of the SRL intervention on both learners' course completion as well as on learners' SRL. Learners' SRL was measured with trace data variables indicating SRL activity. The results showed that the intervention positively affected learners' course completion. Furthermore, the learners who complied with the intervention also engaged in more SRL activities compared to the learners in the control condition: learners who complied showed more metacognitive activities before learning (planning), help seeking, and persistence. Intervention compliance was however low. Further analyses exploring potential causes of the low intervention compliance were conducted. The great majority of learners who did not comply with the intervention dropped out of the MOOC before they encountered the implemented intervention. We conclude that the SRL intervention has been successful in supporting both learners' SRL as well as their course completion. Implications include the importance of supporting learners' SRL as well as the necessity to conduct further research on how to improve intervention compliance.

Developing an Effective Model of Students' Communities of Practice in a Higher Education Context

The purpose of this research is to build an effective model for communities of practice (CoPs) in higher education. This research was designed to a) investigate core factors facilitating organizational learning process among CoP members and b) propose a systematic CoP model for higher education from a learning organization standpoint. A thematic analysis approach was used based on the open-ended responses of 212 CoP program participants at a South Korean university. The results showed that self-regulated learning activities, positive learning perception, and self-participation were found to be core elements for successful CoP activities at the individual level. At the group level, problem-based learning, facilitator, and collaborative learning environments were revealed as key factors for effective organizational learning. Administrative support, systematic learning support, and overall learning culture were found to be the most important influential environmental factors at the organizational level. The study findings imply that the goals, learning processes, and evaluation systems at the higher education level are fundamentally different from those in industrial settings, and conclude that more customized approaches and supporting efforts should be considered in facilitating CoP activities. Research limitations and future research suggestions are proposed based on the study findings.